The Role of Financial Decision-Making Efficiency in SME Growth and Business Sustainability in Pakistan

Abstract

This study investigates the role of financial decision-making efficiency in SME growth and business sustainability in Pakistan. Although small and medium enterprises (SMEs) contribute to economic development, their performance and long-term viability may depend partly on the effectiveness of their financial management practices. Using a quantitative, cross-sectional survey design, primary data were collected from 320 SME owners and managers operating in the manufacturing, services, and trading sectors in Lahore, Karachi, and Islamabad. Data were analysed using SPSS and SmartPLS through descriptive statistics, reliability analysis, correlation analysis, and partial least squares structural equation modelling (PLS-SEM). Financial decision-making efficiency was conceptualized through three dimensions: budgeting efficiency, investment appraisal, and working capital management. The findings indicate that financial decision-making efficiency is positively and significantly associated with SME growth (β = 0.487, p < 0.001) and business sustainability (β = 0.523, p < 0.001). Financial literacy also positively moderates both relationships, suggesting that financial knowledge strengthens the association between efficient financial decision-making and business outcomes. The study highlights the importance of effective financial management practices and financial literacy for SME development and provides relevant insights for SME managers and policymakers seeking to strengthen financial capabilities and support sustainable business performance in Pakistan.

References

Ahangar, N. (2021). Is the relationship between working capital management and firm profitability non-linear in Indian SMEs? Small Enterprise Research, 28(1), 23–35. https://doi.org/10.1080/13215906.2021.1872685

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T

Al Kium, A., Sarker, S., Shikha, S. A., Kamal, M. A. T., Jabed, M. I. K., Munifa, N. K., ... & John, D. B. (2023). Health equity and digital disparities in cancer screening and cardiovascular care across socioeconomic and ethnic groups: A systematic review. Vascular and Endovascular Review, 6(2), 35–44.

Ali, H., Dil, R., Hanif, M., & Saeemab, K. (2025). Socioeconomic determinants influencing the adoption of renewable energy technologies among small and medium enterprises: A field study from Faisalabad, Pakistan. Urban-Rural Community Studies, 1(2), 1–7.

Ali, H., Dil, R., Mustafa, A., Nondani, A., Rajar, L., & Baig, A. (2025). Digitalization and economic growth in Pakistan: An empirical analysis of the services sector (2010–2024). Journal of Media Horizons, 6(5), 649–663. https://jmhorizons.com/index.php/journal/article/view/834

Anwar, M., Shuangjie, L., & Ullah, R. (2020). Business experience or financial literacy? Which one is better for opportunity recognition and superior performance? Business Strategy & Development, 3, 377–387. https://doi.org/10.1002/bsd2.103

Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99–120. https://doi.org/10.1177/014920639101700108

Beck, T., & Demirgüç-Kunt, A. (2006). Small and medium-size enterprises: Access to finance as a growth constraint. Journal of Banking & Finance, 30(11), 2931–2943. https://doi.org/10.1016/j.bankfin.2006.05.009

Berger, A. N., & Udell, G. F. (1998). The economics of small business finance: The roles of private equity and debt markets in the financial growth cycle. Journal of Banking & Finance, 22(6–8), 613–673. https://doi.org/10.1016/S0378-4266(98)00038-7

Brigham, E. F., & Houston, J. F. (2019). Fundamentals of financial management (15th ed.). Cengage Learning.

Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334. https://doi.org/10.1007/BF02310555

Deloof, M. (2003). Does working capital management affect profitability of Belgian firms? Journal of Business Finance & Accounting, 30(3–4), 573–588. https://doi.org/10.1111/1468-5957.00008

Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104

Gomes, C. A., Jabed, M. I. K., Ahmamad, T., Mandal, S., Hassan, S., Sejan, M. K., ... & Jamali, M. L. (2025). Operational and financial evidence for generative AI in United States healthcare administrative workflows. Frontiers in Computer Science and Artificial Intelligence, 4(4), 138–145.

Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.

Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115–135. https://doi.org/10.1007/s11747-014-0403-8

Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. In R. R. Sinkovics & P. N. Ghauri (Eds.), New challenges to international marketing (pp. 277–319). Emerald Group Publishing. https://doi.org/10.1108/S1474-7979(2009)0000020014

Jabed, M. I. K. (2024). Stock market price prediction using machine learning techniques. American International Journal of Sciences and Engineering Research, 7(1), 1–6.

Jabed, M. I. K., Sirazy, M. R. M., Mandal, S., Akter, S., Hassan, A., & Esa, H. (2026). Developing AI-based financial forecasting and cybersecurity systems for the US digital economy. Frontiers in Computer Science and Artificial Intelligence, 5(5), 30–38.

Klapper, L., Lusardi, A., & Panos, G. A. (2013). Financial literacy and its consequences: Evidence from Russia during the financial crisis. Journal of Banking & Finance, 37(10), 3904–3923. https://doi.org/10.1016/j.jbankfin.2013.07.014

Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). Guilford Press.

Kumar, S., Wasim, S. M. S., & Mehmood, S. (2026). From budgets to better decisions: How management controls drive SME financial performance under competitive pressure. Journal of Finance & Economics Research, 11(1). https://doi.org/10.20547/jfer2611103

Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: Theory and evidence. Journal of Economic Literature, 52(1), 5–44. https://doi.org/10.1257/jel.52.1.5

Lusardi, A., & Mitchell, O. S. (2023). The importance of financial literacy: Opening a new field. Journal of Economic Perspectives, 37(4), 137–154. https://doi.org/10.1257/jep.37.4.137

1. V., Almuraqab, N., Moonesar, I. A., Braendle, U. C., & Rao, A. (2024). How critical is SME financial literacy and digital financial access for financial and economic development in the expanded BRICS block? Frontiers in Big Data, 7, Article 1448571. https://doi.org/10.3389/fdata.2024.1448571

Mahmood-ul-Hasan, Saeemab, K., & Ali, H. (2025). Fiscal decentralization, public debt dynamics, and economic growth: Empirical evidence from selected South Asian economies. Social Science Review Archives, 3(3), 2594–2610. https://doi.org/10.70670/sra.v3i3.1386

Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.

Organisation for Economic Co-operation and Development. (2020). OECD/INFE 2020 international survey of adult financial literacy. OECD Publishing. https://doi.org/10.1787/145f5607-en

Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879–903. https://doi.org/10.1037/0021-9010.88.5.879

Ponduru, P. S. (2023). Road accident prediction using lstm gru neural networks (Doctoral dissertation, California State University, Northridge).

Rahman, M. A., Devnath, R. K., Niloy, S. B., Mehedi, C. M., Chowdhury, T. H., & Jabed, M. I. K. (2025, October). A stacking ensemble framework for predicting employee turnover: Explainable AI with SHAP. In 2025 IEEE 2nd International Conference on Computing, Applications and Systems (COMPAS) (pp. 1–6). IEEE.

Saeed, L., Kumar, N., Zeb, A., Riaz, T., & Ali, H. (2025). The impact of sustainability initiatives on corporate financial performance: A quantitative analysis. The Critical Review of Social Sciences Studies, 3(2), 1983–1997.

Small and Medium Enterprises Development Authority. (n.d.). Small and Medium Enterprises Development Authority. https://smeda.org/

Small and Medium Enterprises Development Authority. (n.d.). Financial services. https://smeda.org/index.php?Itemid=116&id=14&option=com_content&view=article

Wiklund, J., & Shepherd, D. (2005). Entrepreneurial orientation and small business performance: A configurational approach. Journal of Business Venturing, 20(1), 71–91. https://doi.org/10.1016/j.jbusvent.2004.01.001

World Bank. (n.d.). SME finance. https://www.worldbank.org/en/topic/smefinance